5 mistakes companies make on AI policy
A Financial Management magazine piece identifies five common mistakes companies make when developing AI policy, pointing to gaps in how organizations approach governance as they move from AI experimentation to operational deployment.
Why this matters: Most companies are writing AI policy for the first time, under real pressure, with no clear model to follow. That is a recipe for rules that look good on paper and fail in practice. The mistakes that matter most are not technical. They are about who is accountable, what decisions get documented, and whether the policy actually changes behavior or just sits in a drawer. Getting this wrong does not just create legal exposure. It means real decisions affecting real people get made without any meaningful oversight.
Who should care: AI governance · Lawyers · Administrators · General readers · Policy
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